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Hai-jun Huang - One of the best experts on this subject based on the ideXlab platform.

  • Modeling the social-influence-based route Choice Behavior in a two-route network
    Physica A: Statistical Mechanics and its Applications, 2019
    Co-Authors: Zhao-ze Zhang, Tie-qiao Tang, Hai-jun Huang
    Abstract:

    Abstract In this paper, we first propose an instance-based learning theory (IBLT) model with social learning to study the day-to-day route Choice Behavior in a two-route network. We then define four indexes (i.e., efficiency, stability, cooperation, and equity) to investigate the effects of social learning on each traffic participant’s route Choice Behavior in a two-route network. Numerical results show that social influence has some positive impacts on route Choice Behavior when more participants select the recommended routes. Cooperation among participants requires them to change their route Choice Behaviors against their natural tendencies. When each participant is very conscious of other participants’ route Choice Behaviors, it can alleviate the above phenomenon.

  • experiment of boundedly rational route Choice Behavior and the model under satisficing rule
    Transportation Research Part C-emerging Technologies, 2016
    Co-Authors: Chuanlin Zhao, Hai-jun Huang
    Abstract:

    Abstract In this paper, we study the boundedly rational route Choice Behavior under the Simon’s satisficing rule. A laboratory experiment was carried out to verify the participants’ boundedly rational route Choice Behavior. By introducing the concept of aspiration level which is specific to each person, we develop a novel model of the problem in a parallel-link network and investigate the properties of the boundedly rational user equilibrium (BRUE) state. Conditions for ensuring the existence and uniqueness of the BRUE solution are derived. A solution method is proposed to find the unique BRUE state. Extensions to general networks are conducted. Numerical examples are presented to demonstrate the theoretical analyses.

  • experiment of boundedly rational route Choice Behavior and the model under satisficing rule
    International Conference on Intelligent Transportation Systems, 2014
    Co-Authors: Chuanlin Zhao, Hai-jun Huang
    Abstract:

    In this paper, the authors study the boundedly rational route Choice Behavior under the Simon's satisficing rule. A laboratory experiment is presented to verify the participants' boundedly rational route Choice Behavior. By introducing the concept of aspiration level which is specific to each person, the authors develop a novel model of the problem in a parallel-link network and derive the properties of boundedly rational user equilibrium (BRUE) state. Conditions for ensuring the existence and uniqueness of the BRUE solution are derived. A solution method is proposed to find the unique BRUE state. Numerical examples are presented to demonstrate the theoretical analyses.

Tomio Miwa - One of the best experts on this subject based on the ideXlab platform.

  • Preliminary analysis on dynamic route Choice Behavior : Using probe-vehicle data
    Journal of Advanced Transportation, 2006
    Co-Authors: Taka Morikawa, Tomio Miwa
    Abstract:

    Dynamic traffic assignment models have been attracting increasing attention with the progress of traffic management policies based on information technology. These dynamic estimation tools, however, just apply static route Choice models either at only origin node or at every arrival node. This paper aims at providing some knowledge on drivers' dynamic route Choice Behavior using probe-vehicle data. The results of analyses show that route Choice Behavior relates to the distance from driver's position to the destination and that dynamic route Choice Behavior is modeled better by considering decision process during the trip.

  • Analyses on Dynamic Route Choice Behavior Using Probe-Vehicle Data
    2005
    Co-Authors: Tomio Miwa
    Abstract:

    Dynamic traffic assignment models have been attracting increasing attention with the progress of traffic management policies based on information technology. These dynamic estimation tools, however, just apply static route Choice models either at only origin node or at every arrival node. This paper aims at providing some knowledge on drivers’ dynamic route Choice Behavior using probe-vehicle data. The results of analyses show that route Choice Behavior relates to the distance from driver’s position to the destination and that dynamic route Choice Behavior is modeled better by considering decision process during the trip.

  • The Model Analysis on Route Choice Behavior based on Probe-Car Data
    INFRASTRUCTURE PLANNING REVIEW, 2004
    Co-Authors: Tomio Miwa, Takayuki Morikawa
    Abstract:

    Analysis on route Choice Behavior is the key to analyzing travel Behavior and traffic demand on road networks. The data from the probe-car systems are very useful for making it clear. In this study we analyze the route Choice Behaviors, especially the accuracy of the travel time information drivers use for route choicc and the fits of several route Choice models The result indicates that drivers use rather rough information on expected travel conditions for route Choice, and that necessity of analysis on dynamic route Choice Behavior and framework of route Choice process.

Yang Yang - One of the best experts on this subject based on the ideXlab platform.

  • Modeling the charging and route Choice Behavior of BEV drivers
    Transportation Research Part C: Emerging Technologies, 2016
    Co-Authors: Yang Yang, En Jian Yao, Zhiqiang Yang, Rui Zhang
    Abstract:

    Due to the limited cruising range of battery electric vehicle (BEV), BEV drivers show obvious difference in travel Behavior from gasoline vehicle (GV) drivers. To analyze BEV drivers’ charging and route Choice Behaviors, and extract the differences between BEV and GV drivers’ travel Behavior, two multinomial logit-based and two nested logit-based models are proposed in this study based on a stated preference survey. The nested structure consists of two levels: the upper level represents the charging decision, and the lower level shows the route Choices corresponding to the charging and no-charging situations respectively. The estimated results demonstrate that the nested structure is more appropriate than the multinomial structure. Meanwhile, it is observed that the initial state of charge (SOC) at origin of BEV is the most important factor that affects the decision of charging or not, and the SOC at destination becomes an important impact factor affecting BEV drivers’ route Choice Behavior. As for the route Choice Behavior when BEV has charging demand, the charging station attributes such as charging time and charging station’s location have significant influences on BEV drivers’ decision-making process. The results also show that BEV drivers incline to choose the routes with charging station having less charging time, being closer to origin and consistent with travel direction. Finally, based on the proposed models, a series of numerical analysis has been conducted to verify the effect of range anxiety on BEV charging and route Choice Behavior and to reveal the variation of comfortable initial SOC at origin with travel distance. Meanwhile, the effects of charging time and distance from origin to charging station also have been discussed.

  • Drivers’ Route Choice Behavior Analysis Based on Cumulative Prospect Theory
    Advanced Materials Research, 2014
    Co-Authors: Wei Yan Zong, En Jian Yao, Yang Yang
    Abstract:

    Due to different travel experiences, travel attitude varies from people of different levels of familiarity with urban route network. Expected utility theory (EUT) is usually used to describe travelers’ route Choice Behavior. But there is huge discrepancy between reality and the results under the condition with network uncertainty when the cumulative prospect theory (CPT) is more attractive to describe the travelers’ route Choice Behavior. Based on CPT this study designs scenarios at different levels of familiarity with urban road network, analyzes route Choice Behavior in all scenarios and conclude travelers’ Behavior characteristics compared with reality investigation results. It shows that CPT is really more powerful to describe the travelers’ Behavior under risk and people of high familiarity level are more relied on constraint time and tend to take a risk for more gain.

Chuanlin Zhao - One of the best experts on this subject based on the ideXlab platform.

  • experiment of boundedly rational route Choice Behavior and the model under satisficing rule
    Transportation Research Part C-emerging Technologies, 2016
    Co-Authors: Chuanlin Zhao, Hai-jun Huang
    Abstract:

    Abstract In this paper, we study the boundedly rational route Choice Behavior under the Simon’s satisficing rule. A laboratory experiment was carried out to verify the participants’ boundedly rational route Choice Behavior. By introducing the concept of aspiration level which is specific to each person, we develop a novel model of the problem in a parallel-link network and investigate the properties of the boundedly rational user equilibrium (BRUE) state. Conditions for ensuring the existence and uniqueness of the BRUE solution are derived. A solution method is proposed to find the unique BRUE state. Extensions to general networks are conducted. Numerical examples are presented to demonstrate the theoretical analyses.

  • experiment of boundedly rational route Choice Behavior and the model under satisficing rule
    International Conference on Intelligent Transportation Systems, 2014
    Co-Authors: Chuanlin Zhao, Hai-jun Huang
    Abstract:

    In this paper, the authors study the boundedly rational route Choice Behavior under the Simon's satisficing rule. A laboratory experiment is presented to verify the participants' boundedly rational route Choice Behavior. By introducing the concept of aspiration level which is specific to each person, the authors develop a novel model of the problem in a parallel-link network and derive the properties of boundedly rational user equilibrium (BRUE) state. Conditions for ensuring the existence and uniqueness of the BRUE solution are derived. A solution method is proposed to find the unique BRUE state. Numerical examples are presented to demonstrate the theoretical analyses.

Haiying Li - One of the best experts on this subject based on the ideXlab platform.

  • learning the route Choice Behavior of subway passengers from afc data
    Expert Systems With Applications, 2018
    Co-Authors: Xinyue Xu, Haiying Li
    Abstract:

    Abstract This paper learns the route Choice Behavior of passengers from Auto Fare Collection, timetable, and train loading data using a method combined with Bayesian inference and Metropolis-Hasting sampling. First, the influential factors of route Choice such as in-vehicle travel time, transfer time, and in-vehicle crowding are given. Next, formulations are established based on AFC, timetable and train loading data, which are merged into a logit model of route Choice Behavior of subway passengers. Next, an algorithm integrating Bayesian inference and Metropolis-Hasting sampling is designed to calibrate parameters of the logit model. Finally, a case study of Beijing subway is applied to verify the validity of the model and algorithm. A detailed discussion shows that in-vehicle crowding plays a crucial role in passenger route Choice Behavior.